What are the fundraising trends in the AI knowledge and search market?
In our updated market reports, you will find everything you need
SUMMARY
We analyzed publicly disclosed equity funding rounds in the AI knowledge and search market across 2024, 2025, and year-to-date 2026, using a strict pure-play filter for companies that retrieve, organize, summarize, or answer questions from information sources. The covered scope includes Enterprise Search, AI Knowledge Bases, Retrieval Augmented Generation, Document Intelligence, Research Assistants, Semantic Search APIs, Knowledge Graph Tools, and Answer Engines.
The market has cooled in total dollars since the 2024 peak. Funding fell from about $2.19B in 2024 to about $1.24B in 2025, then reached about $496M through early July 2026, versus about $769M over the comparable period in 2025.
The decline is not mainly a collapse in company activity. Full-year deal count was almost flat from 17 deals in 2024 to 18 deals in 2025, while capital fell by roughly 43%, which means the market changed because rounds got smaller and fewer giant financings appeared.
The AI knowledge and search market remains highly concentrated. In 2024, the top 3 deals captured about 64% of capital; in 2025, the top 3 captured about 60%; and through early July 2026, the top 3 captured about 81%.
The category leader has rotated each year. Enterprise Search led in 2024, Answer Engines led in 2025, and Semantic Search APIs dominate year-to-date 2026 with roughly 90% of all capital raised so far.
Capital is moving down the stack toward retrieval infrastructure. The strongest 2026 rounds are concentrated around companies that help AI systems search the web, retrieve information, rank results, structure context, or power AI agents.
The market is late-stage by dollars but still experimental at the edges. In 2025, Series B and later rounds captured about 89% of capital, and through early July 2026 they captured about 98%.
New startups are still entering the AI knowledge and search market, but they are not where most capital is going. First financings represented about 22% of 2025 deals and 25% of early-2026 deals, but only about 2% of 2025 capital and less than 1% of early-2026 capital.
North America remains the scale-financing hub. It captured about 99.6% of full-year 2025 capital and about 71% of capital through early July 2026, even as Europe, Asia-Pacific, and the Middle East became more visible by deal count in 2026.
The practical interpretation is that the AI knowledge and search market is not disappearing. It is becoming more selective, more infrastructure-led, and more winner-takes-most, with investors backing fewer companies that look like core information-access layers for AI systems.
Is more or less capital going into the AI knowledge and search market?
Less capital is going into the AI knowledge and search market, both on the full-year comparison and on the freshest year-to-date comparison. Funding fell from about $2.19B in 2024 to about $1.24B in 2025, a decline of roughly 43%, and funding through early July 2026 reached about $496M versus about $769M over the comparable period in 2025.
That makes the cooling hard to dismiss as a timing artifact. Full-year 2025 was down versus full-year 2024, and the first part of 2026 is also down versus the same part of 2025. When both the reliable full-year comparison and the fresh year-to-date comparison point in the same direction, the stronger reading is that the market has moved past the 2024 peak.
The AI knowledge and search market is not being abandoned, though. The 2026 year-to-date total still comes from only 8 qualifying deals, and the median round is about $43.5M, which is high for a young software market. Investors are still writing serious checks when they believe a company controls a critical retrieval, search, or context layer.
The right interpretation is not that the AI knowledge and search market has lost relevance. The better interpretation is that capital has become more selective. The market no longer funds every AI search or RAG narrative equally; it rewards companies with proof of distribution, infrastructure depth, developer adoption, enterprise integration, or control over valuable information access.
Is AI knowledge and search funding activity driven by more deals or larger rounds?
AI knowledge and search funding activity is driven more by larger rounds than by more deals. The clearest evidence is the full-year comparison: deal count rose slightly from 17 deals in 2024 to 18 deals in 2025, but total capital fell from about $2.19B to about $1.24B.
That means the 2025 decline was not caused by fewer companies raising money. It was caused by smaller rounds and fewer outsized financings. Average round size fell from about $129M in 2024 to about $69M in 2025, while median round size fell from $55M to about $24M.
The freshest comparison confirms the same pattern with a small twist. Through early July 2026, the market had 8 deals, compared with 7 deals over the comparable period in 2025, so deal count is slightly higher. Yet capital fell from about $769M to about $496M, which means the current market is not weaker because fewer deals happened; it is weaker because the largest 2025 outlier was bigger.
The nuance is that the 2026 median round is higher than the comparable 2025 median, about $43.5M versus about $24.5M. That suggests the typical disclosed 2026 deal is not small. But the 2025 comparable period included Perplexity’s $500M financing, which lifted the total and the average. So the AI knowledge and search market is active, but total dollars still depend heavily on whether one or two mega-rounds appear.
Is AI knowledge and search capital moving toward later-stage or earlier-stage companies?
AI knowledge and search capital is moving decisively toward later-stage companies, even though early-stage startups still appear in the deal count. In 2025, Seed plus Series A rounds captured only about 11% of capital, while Series B and later captured about 89%; through early July 2026, Seed plus Series A captured only about 2%, while Series B and later captured about 98%.
The full-year comparison shows this is not new. In 2024, about 95% of capital went to Series B or later. In 2025, the early-stage share improved slightly, but the market was still overwhelmingly late-stage by dollars.
The 2026 year-to-date stage mix is especially concentrated. Series C captured $250M, Series B captured $237M, and Seed captured only $8.6M. There were no qualifying Series A deals through early July 2026.
The practical reading is that investors are no longer primarily asking whether AI knowledge and search can work. They are asking which companies already have enough validation to become infrastructure layers, enterprise systems, or default retrieval providers for AI applications.
Is the AI knowledge and search market maturing or still experimental?
The AI knowledge and search market is maturing by capital allocation, but it remains experimental at the edges. The largest dollars are going to mature infrastructure and platform companies, while smaller first financings are still testing new wedges such as knowledge graphs, answer-engine optimization, and vertical document intelligence.
The strongest maturity signal is the late-stage capital share. Series B and later rounds captured about 95% of 2024 capital, about 89% of 2025 capital, and about 98% of year-to-date 2026 capital. That is not a seed-led market; it is a market where investors believe several control points are already visible.
The category rotation also shows maturation. In 2024, Enterprise Search and Answer Engines captured the largest dollars. In 2025, Answer Engines dominated because Perplexity and You.com attracted large rounds. In 2026 so far, Semantic Search APIs dominate because investors are funding the infrastructure that lets AI systems retrieve live, structured, searchable information.
The experimental layer still matters, but it is not the economic center. First financings represented about 25% of early-2026 deals but less than 1% of capital. The AI knowledge and search market is still producing new ideas, but the money is flowing to companies that already look strategically important.
Are new startups still entering the AI knowledge and search market?
Yes, new startups are still entering the AI knowledge and search market, but they are capturing very little capital. First financings represented about 22% of 2025 deals and about 25% of early-2026 deals, so startup formation is clearly still happening.
The capital share tells a different story. In 2025, first financings captured only about 2% of total capital. Through early July 2026, first financings captured less than 1% of capital. That means new companies are entering through small checks while most dollars go to follow-on rounds.
The types of new entrants also matter. The 2026 first financings were in narrower or emerging categories, such as codebase knowledge graphs and answer-engine optimization. These are edge opportunities, not the core capital pools of the market.
The AI knowledge and search market is therefore not closed to new entrants, but it is not a broad seed-stage land grab. Investors are using small early rounds to test new surfaces while reserving large checks for companies with proven technical depth, distribution, or enterprise relevance.
Are more investors entering the AI knowledge and search market?
More investors appear to be entering the AI knowledge and search market in the freshest year-to-date comparison, but the more reliable full-year comparison shows investor participation cooled from the 2024 peak. Total unique investors fell from 83 in 2024 to 67 in 2025, and unique tier-1 investors fell from 33 to 26.
The early-2026 signal is more positive. Through early July 2026, the market had 34 unique disclosed investors and 13 unique tier-1 investors, compared with 28 unique investors and 10 tier-1 investors over the comparable period in 2025. That suggests investor breadth has improved recently, despite lower total capital.
This should be read carefully because the 2026 sample is still small. A few syndicates around Exa, Parallel, Qdrant, Nimble, and Dust can make investor breadth look healthier than the underlying market really is.
The better interpretation is that investor interest has not vanished, but it has narrowed around specific theses. Investors are not broadly flooding every AI knowledge app. They are showing up around retrieval infrastructure, live web access, semantic search, vector search, and enterprise context layers.
Are top investors getting more or less active in the AI knowledge and search market?
Top investors are getting more selective in the AI knowledge and search market rather than simply more or less active. Elite firms are still present, but repeat top-investor activity is narrower in 2026 than it was during the 2024 peak.
In 2024, repeat participation was broad. IVP and NEA appeared in 4 deals each, NVIDIA and Databricks Ventures appeared in 3 deals each, and Lightspeed also appeared in 3 deals. That pattern reflected a wide elite-investor appetite across answer engines, enterprise search, RAG, and semantic search.
In 2025, Y Combinator became the most frequent repeat investor with 8 deals, while Benchmark appeared in 3. That shifted the repeat-investor pattern toward the early-stage and infrastructure pipeline rather than broad late-stage participation.
Through early July 2026, only Sequoia and Spark Capital appeared more than once among named repeat investors. Other top names such as Andreessen Horowitz, Benchmark, Lightspeed, Y Combinator, Kleiner Perkins, Index Ventures, Khosla Ventures, First Round Capital, Norwest, Databricks Ventures, and Snowflake Ventures are still visible, but mostly in single deals.
The practical takeaway is that top investors have not left the AI knowledge and search market. They are concentrating their conviction around fewer companies and fewer layers, especially companies that look like core retrieval infrastructure for AI systems.
Which AI knowledge and search subcategories are gaining momentum?
Semantic Search APIs are the clearest subcategory gaining momentum in the AI knowledge and search market. The category grew from about $50M in 2024 to about $120M in 2025, then surged to about $447M through early July 2026.
The capital share shift is even more dramatic. Semantic Search APIs represented about 2% of 2024 capital, about 10% of 2025 capital, and about 90% of early-2026 capital. That is the strongest category rotation in the entire market.
The reason is that Semantic Search APIs are increasingly being framed as infrastructure for AI agents and AI applications, not as human search tools. Exa, Parallel, Qdrant, and Nimble all sit in the layer that helps AI systems retrieve, rank, structure, and use external information.
Document Intelligence also gained structural credibility between 2024 and 2025. It raised about $101M in 2024 and about $116.5M in 2025, with Reducto raising twice in 2025. The 2026 year-to-date figure is much smaller, but the category’s prior follow-on activity suggests investor confidence in document parsing and ingestion as a real bottleneck.
AI Knowledge Bases also reappeared in 2026 through Dust’s $40M Series B after no qualifying 2025 deal in that category. That is not enough to prove broad acceleration, but it suggests enterprise context layers remain investable when they connect knowledge bases to collaboration and human-agent workflows.
Which AI knowledge and search subcategories are losing momentum?
Enterprise Search and Answer Engines are losing momentum in the freshest 2026 comparison, while Research Assistants and explicit Retrieval Augmented Generation look quieter but require more careful interpretation. The strongest decline is Enterprise Search, which fell from about $1.11B in 2024 to about $180M in 2025 and has no qualifying pure-play deal through early July 2026.
Enterprise Search may not be structurally weak; it may be post-mega-round. Glean and AlphaSense already raised very large rounds in 2024 and 2025, so the absence of early-2026 Enterprise Search funding may reflect prior capitalization rather than lower enterprise demand.
Answer Engines also look much weaker in 2026 so far. The category raised about $636M in 2024 and about $750M in 2025, but only about $1.8M through early July 2026. That suggests the marginal investor dollar has moved away from answer interfaces and toward search infrastructure.
Research Assistants had $141.5M in 2024 and $72.5M in 2025, but no qualifying early-2026 deal. That may mean the category has slowed, or it may mean research-assistant functionality is being absorbed into broader vertical AI, workflow, or enterprise knowledge tools that do not pass the strict pure-play filter.
Retrieval Augmented Generation as an explicit category also looks weaker by label. It raised $93M in 2024, $4.2M in 2025, and zero through early July 2026. But this is partly semantic: RAG as a label is fading while the underlying retrieval problem is being funded inside Semantic Search APIs, Document Intelligence, and agentic web infrastructure.
Which regions are gaining momentum in AI knowledge and search funding?
Europe and the Middle East are gaining momentum in AI knowledge and search funding, while North America remains the dominant region. The 2026 year-to-date regional split is more diverse than the 2025 full-year pattern, even though the biggest checks still concentrate in North America.
In 2025, North America captured about 99.6% of capital and 94% of deals, while Europe captured only one small deal and less than 1% of capital. Asia-Pacific, Latin America, the Middle East, and Africa had no qualifying 2025 capital in the strict screen.
Through early July 2026, Europe rose to about $90M, or 18% of capital, through Qdrant and Dust. That is the strongest regional improvement outside North America. The Middle East also appeared with Nimble’s $47M Series B, equal to about 9% of early-2026 capital.
Asia-Pacific also reappeared in deal count through Potpie and Mary Technology, but the capital total was only about $6.8M. So Asia-Pacific is gaining visibility as an experimentation region, while Europe and the Middle East are gaining more meaningful scaling visibility.
Which regions are losing momentum in AI knowledge and search funding?
North America is losing share in AI knowledge and search funding in the freshest comparison, but it is not losing leadership. North America captured about 99.6% of full-year 2025 capital and about 99.3% of capital over the comparable early-2025 period, then fell to about 71% through early July 2026.
That decline in share should not be misread as absolute weakness. North American companies still raised about $352M through early July 2026, including Exa’s $250M Series C and Parallel’s $100M Series B. North America also had the highest regional median round at about $100M.
Asia-Pacific is weaker in capital terms than it was in 2024. In 2024, Asia-Pacific raised about $101M across two Document Intelligence deals; in 2025, it had no qualifying deals; and through early July 2026, it had two deals but only about $6.8M.
Latin America and Africa remain absent from the qualifying market across 2024, 2025, and early 2026. That absence matters because the AI knowledge and search market is not yet showing broad global venture formation across all major regions.
Is the AI knowledge and search market becoming more global or more regionally concentrated?
The AI knowledge and search market is becoming more global by deal distribution, but it remains regionally concentrated by capital. The 2026 year-to-date market is more geographically diverse than 2025, but North America still controls the largest rounds.
The full-year 2025 market was extremely concentrated. North America had 17 of 18 deals and about 99.6% of capital. Europe had only one small deal, and no other region had qualifying capital.
The early-2026 market is more global. North America has 3 of 8 deals, Europe has 2, Asia-Pacific has 2, and the Middle East has 1. That is a much broader footprint by deal count.
The capital split tells the more important story. North America still has about 71% of dollars, Europe has about 18%, the Middle East has about 9%, and Asia-Pacific has only about 1%. The market is globalizing at the edges, but scale financing remains concentrated around North American companies and North American-led investor networks.
Is AI knowledge and search capital moving toward proven winners or new opportunities?
AI knowledge and search capital is moving overwhelmingly toward proven winners, while new opportunities receive smaller exploratory checks. In 2025, first financings represented about 22% of deals but only about 2% of capital; through early July 2026, first financings represented 25% of deals but less than 1% of capital.
The stage mix confirms the same point. Through early July 2026, Series B and Series C rounds captured about 98% of capital. The largest checks went to Exa, Parallel, Qdrant, Nimble, and Dust, all follow-on rounds.
That means the AI knowledge and search market is not a seed-led land grab. Investors are still testing new wedges, but the large pools of capital are being reserved for companies that already look validated.
The clearest rule is that funding follows proof of control. Companies that control developer adoption, enterprise context, live web access, search infrastructure, or retrieval quality are much more likely to attract large follow-on rounds than companies with only a broad AI search narrative.
Is the AI knowledge and search market becoming winner-takes-most?
Yes, the AI knowledge and search market is becoming winner-takes-most, although not necessarily winner-takes-all. Capital concentration is extreme across every year reviewed, and the largest rounds determine the market narrative.
In 2024, the top 3 deals captured about 64% of total capital, and the top 10 captured about 93%. In 2025, the top 3 captured about 60%, and the top 10 captured about 92%. Through early July 2026, the top 3 captured about 81%, and the top 5 captured about 98%.
The bottom half of deals consistently receives little capital. The bottom 50% captured about 9% of 2024 capital, about 10% of 2025 capital, and about 10% of early-2026 capital. That stability is important because it shows concentration is structural, not a one-year anomaly.
The market is winner-takes-most by category layer. In 2024, AlphaSense, Glean, and Perplexity shaped the market. In 2025, Perplexity, Glean, You.com, Exa, and Reducto shaped the market. In 2026 so far, Exa, Parallel, Qdrant, Nimble, and Dust shape the market. The winners change, but the concentration pattern remains.
Is the next wave of AI knowledge and search winners becoming visible?
Yes, the next wave of AI knowledge and search winners is becoming visible, and it is concentrated around AI search infrastructure rather than classic enterprise search or consumer answer engines. The clearest 2026 candidates are Exa, Parallel Web Systems, Qdrant, Nimble, and Dust.
The reason is not just that these companies raised money. They raised large follow-on rounds in the category where investor attention is shifting. Semantic Search APIs captured about $447M, or roughly 90% of early-2026 capital.
This next wave looks different from the 2024 wave. The 2024 leaders were mainly Enterprise Search, market intelligence, and Answer Engine companies such as AlphaSense, Glean, and Perplexity. The 2026 leaders are more infrastructure-oriented, helping AI systems retrieve, rank, verify, and use external information.
The caution is that visibility is not inevitability. Large rounds can overstate durability. But compared with thinly funded seed companies and inactive categories, the 2026 infrastructure companies have stronger investor validation, larger capital bases, and clearer strategic relevance to the AI stack.
Is the AI knowledge and search funding landscape fragmenting or consolidating?
The AI knowledge and search funding landscape is consolidating by capital but fragmenting by product surface. Money is concentrating into a small number of large winners, while the funded product map keeps spreading across search APIs, document intelligence, knowledge graphs, knowledge bases, answer engines, and agentic web retrieval.
Capital concentration is the consolidation signal. Through early July 2026, the top 3 deals captured about 81% of capital, and the top 5 captured about 98%. In 2024 and 2025, the top 10 captured more than 92% of capital in both years.
The product surface is the fragmentation signal. The market has rotated from Enterprise Search and Answer Engines in 2024, to Answer Engines plus Document Intelligence and Semantic Search APIs in 2025, to a Semantic Search API-led market in 2026.
The best description is asymmetric. The language and use cases are fragmenting, but the money is consolidating around companies that look like control layers. That is typical of maturing AI infrastructure markets: more labels appear, while fewer companies capture the capital.
Where is investor attention shifting in the AI knowledge and search market?
Investor attention in the AI knowledge and search market is shifting from user-facing answer products and classic enterprise search toward retrieval infrastructure for AI agents, semantic search APIs, live web access, and context layers. The clearest evidence is that Semantic Search APIs rose from about 2% of capital in 2024 to about 10% in 2025 and about 90% through early July 2026.
The company-level evidence points in the same direction. Exa is building search for AIs, Parallel is building web search and web infrastructure APIs for agents, Nimble is building a web-search agent platform, Qdrant is building vector search infrastructure, and Dust is building an enterprise AI context layer.
This does not mean Enterprise Search and Answer Engines are dead. Glean, AlphaSense, Perplexity, and You.com remain important companies. But the marginal new dollar has moved downward in the stack, toward the systems that make retrieval and grounding possible for many applications.
The strongest interpretation is that the AI knowledge and search market has moved from the question “who owns the answer interface?” toward the question “who owns the information access layer?” That is the central strategic shift in the market.
INSIGHTS
The insights below come from reviewing publicly disclosed equity rounds in the AI knowledge and search market across 2024, 2025, and year-to-date 2026, with a strict pure-play filter for companies built around search, retrieval, knowledge organization, document intelligence, research assistance, semantic search, knowledge graphs, and answer engines.
- The AI knowledge and search market is cooling in total capital but not collapsing in strategic relevance. Funding fell from about $2.19B in 2024 to about $1.24B in 2025, and the early-2026 total is below the comparable 2025 period, but the 2026 median round of about $43.5M still shows real investor conviction for companies that control retrieval layers.
- The market is not deal-count constrained; it is mega-round constrained. Deal count was almost flat from 2024 to 2025, yet capital fell sharply, which proves that the headline funding total depends more on the top few financings than on the number of companies raising.
- The dominant category has changed every year, which means the market is still searching for its most defensible control point. Enterprise Search led by dollars in 2024, Answer Engines led in 2025, and Semantic Search APIs dominate early 2026.
- The biggest strategic shift is from answer ownership to retrieval ownership. In 2024 and 2025, the largest dollars went to companies that delivered answers to users or enterprises; in 2026, the largest dollars are going to companies that help AI systems retrieve information.
- RAG is losing strength as a standalone funding label even though retrieval is becoming more important. The explicit Retrieval Augmented Generation category fell from $93M in 2024 to $4.2M in 2025 and zero in early 2026, while Semantic Search APIs rose sharply over the same period.
- The AI knowledge and search market is mature by capital allocation but experimental by product language. Series B and later rounds dominate dollars, while new labels such as answer-engine optimization, codebase knowledge graphs, and web search for agents continue to appear.
- First financings are useful as a signal of experimentation, not as a signal of where the money is going. In early 2026, first financings represented 25% of deals but less than 1% of capital.
- The real proof standard has shifted from “can the model answer questions?” to “can the system retrieve, structure, rank, verify, and operationalize the right information?” This explains why recent large rounds cluster around Exa, Parallel, Qdrant, Nimble, Dust, and similar infrastructure companies.
- The market is winner-takes-most by financing, even when it is not winner-takes-all by product. The top 10 deals captured more than 92% of capital in both 2024 and 2025, and the top 5 captured about 98% of early-2026 capital.
- The average round size is a weak proxy for the typical company. In 2025, the average round was about $69M while the median was about $24M, showing how heavily outliers shape the headline.
- The 2026 market looks healthier by median round size than by total capital. Total capital is down versus the comparable 2025 period, but the median disclosed round is higher, which suggests fewer blockbuster checks rather than a disappearance of institutional funding.
- The absence of qualifying Series A rounds in early 2026 is a warning sign for the middle of the company-formation funnel. The market has seed experiments and large Series B or Series C rounds, but fewer visible companies in the institutional Series A layer.
- North America remains the scale-financing hub, but 2026 is less geographically one-sided than 2025. North America’s capital share fell from about 99.6% in 2025 to about 71% in early 2026, while Europe and the Middle East became materially visible.
- Europe’s strongest role is technical and enterprise infrastructure rather than consumer answer distribution. Qdrant and Dust show that Europe can produce credible retrieval and enterprise-context companies, but not yet the largest answer-engine financings in this sample.
- Asia-Pacific appears more as an experimentation geography than a scale-financing geography in early 2026. It has 25% of year-to-date deal count but only about 1% of capital.
- The investor base is elite but not deeply repetitive in early 2026. Sequoia and Spark Capital are the only investors appearing more than once, which suggests broad top-tier interest but limited repeat-pattern conviction across many companies.
- The market increasingly rewards infrastructure utilities rather than single-purpose applications. The largest 2026 deals are search, retrieval, vector, web, and context layers that many AI systems can depend on.
- Enterprise Search is not dead; it is post-mega-round. The category fell from $1.11B in 2024 to $179.5M in 2025 and zero in early 2026, but that likely reflects prior large rounds by leaders such as Glean and AlphaSense rather than a collapse in enterprise demand.
- Document Intelligence appears to be moving from horizontal parsing toward workflow-specific funding. Reducto’s 2025 financings validated the horizontal document-intelligence layer, while Mary Technology’s 2026 financing shows a narrower source-linked legal fact-management use case.
- Knowledge Graph Tools are visible but still undercapitalized. Potpie’s $2.2M seed round gives the category a 2026 presence, but the small capital share suggests knowledge graphs remain more of an architectural thesis than a scaled funding category.
- The market’s funding narrative has shifted from “search replacement” to “AI dependency layer.” The most funded 2026 companies matter because agents, copilots, and applications need reliable retrieval infrastructure, not because humans need another search box.
- The strongest diligence rule is to separate interface companies from substrate companies. Interface companies can attract huge rounds when they own user behavior, but substrate companies are gaining momentum because they can serve many downstream AI applications.
- The AI knowledge and search market is now better understood as a stack than as a single category. The stack includes data ingestion, document parsing, vector and semantic retrieval, web search APIs, enterprise permissioning, knowledge and context layers, answer interfaces, and analytics around answer visibility.
OUR METHODOLOGY TO BUILD THIS TRACKER
We built this AI knowledge and search funding tracker by reviewing publicly disclosed equity rounds raised by pure-play companies between January 2024 and July 2026. A company counts as pure-play when more than 80% of its activity is dedicated to retrieving, organizing, summarizing, structuring, or answering questions from information sources.
We applied four core filters. First, we only included equity rounds, so grants, debt, structured financings, acquisitions, and business combinations were excluded. Second, we only counted disclosed rounds of $300K or more. Third, we only kept companies that fit the AI knowledge and search market definition, including Enterprise Search, AI Knowledge Bases, Retrieval Augmented Generation, Document Intelligence, Research Assistants, Semantic Search APIs, Knowledge Graph Tools, and Answer Engines. Fourth, every included deal had to be backed by a direct company announcement, press release, investor announcement, tier-1 media report, specialized industry source, or relevant regional publication.
We excluded adjacent companies where AI knowledge or search was only a feature rather than the core business. That means broad foundation-model companies, generic AI agents, workflow automation tools, customer-support bots, generic vector infrastructure without clear search or RAG positioning, legal-only vertical software outside the strict retrieval/search scope, and answer-engine-optimization tools outside the defined market were excluded unless the raw research explicitly supported inclusion.
Undisclosed-amount rounds were excluded because including them would distort dollar-based metrics such as total capital raised, average round size, category capital share, geography share, and concentration among the largest deals. Privately raised rounds, unannounced SAFEs, paywalled-only financings, and rounds without reliable public amount disclosure may therefore be missing from the tracker.
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